Global retention model based on multisample system parameters for optimising chromatographic fingerprints of medicinal plants.

Background: Developing analytical methods for Traditional Medicine products by liquid chromatography is challenging due to their chemical complexity and the lack of analytical standards for numerous, unidentified constituents. Regulatory agencies recommend chromatographic fingerprint analysis for quality evaluation, relying on peak detection to ensure resolution. Conventional modelling struggles to optimise experimental conditions for such complex samples.

Transferability of global retention models in reversed-phase liquid chromatography for natural products.

Considerable progress has been made in enhancing resolution in reversed-phase liquid chromatography for the analysis of complex samples, particularly within the field of natural products, through the application of global retention models using multi-linear gradients. Global models effectively differentiate solute retention effects from those originating from the column and solvent, offering predictive capabilities comparable to conventional individual retention models, without the requirement for standards for all compounds. While conventional individual models result in higher accuracy, they frequently demand standards that are unavailable for natural product samples.

Performance of global retention models in the optimisation of the liquid chromatographic separation (II): Complex multi-analyte samples.

Background: Enhancing the quality control of medicinal plants is a complex challenge due to their rich variety of chemical compounds present at varying and extreme concentrations. Chromatographic fingerprints, which have become essential for characterising these complex natural materials, require achieving optimal separation conditions to effectively maximise the number of detected peaks. The challenges in optimising fingerprints and other complex multi-analyte samples include the unavailability of standards, the presence of unknown constituents and the substantial workload that would require conventional optimisation methods based on models.

The role of the cation and anion in aqueous liquid chromatography with sodium dodecyl sulphate and imidazolium-based ionic liquids as mobile phase reagents.

Background: In reversed-phase liquid chromatography, solute retention is primarily influenced by interactions between a nonpolar stationary phase and a moderately polar hydro-organic mobile phase, based on the solute lipophilicity. However, challenges regarding retention and peak tailing can arise due to ionic interactions between positively charged analytes and free silanols present on silica-based stationary phases. To address these challenges, incorporating surfactants and ionic liquids (ILs) into the mobile phase offers an effective solution.

Analysis and classification of tea varieties using high-performance liquid chromatography and global retention models.

As a result of their metabolic processes, medicinal plants produce bioactive molecules with significant implications for human health, used directly for treatment or for pharmaceutical development. Chromatographic fingerprints with solvent gradients authenticate and categorise medicinal plants by capturing chemical diversity. This work focuses on optimising tea sample analysis in HPLC, using a model-based approach without requiring standards.